Remote monitoring data from cardiac implantable electronic devices predicts all-cause mortality.

ABSTRACT

AIMS: To determine if remotely monitored physiological data from cardiac implantable electronic devices (CIEDs) can be used to identify patients at high risk of mortality. METHODS AND RESULTS: This study evaluated whether a risk score based on CIED physiological data (Triage-Heart Failure Risk Status, 'Triage-HFRS', previously validated to predict heart failure (HF) events) can identify patients at high risk of death. Four hundred and thirty-nine adults with CIEDs were prospectively enrolled. Primary observed outcome was all-cause mortality (median follow-up 702 days). Several physiological parameters [including heart rate profile, atrial fibrillation/tachycardia (AF/AT) burden, ventricular rate during AT/AF, physical activity, thoracic impedance, therapies for ventricular tachycardia/fibrillation] were continuously monitored by CIEDs and dynamically combined to produce a Triage-HFRS every 24 h. According to transmissions patients were categorized into 'high-risk' or 'never high-risk' groups. During follow-up, 285 patients (65%) had a high-risk episode and 60 patients (14%) died (50 in high-risk group; 10 in never high-risk group). Significantly more cardiovascular deaths were observed in the high-risk group, with mortality rates across groups of high vs. never-high 10.3% vs. <4.0%; P = 0.03. Experiencing any high-risk episode was associated with a substantially increased risk of death [odds ratio (OR) 3.07, 95% confidence interval (CI) 1.57-6.58, P = 0.002]. Furthermore, each high-risk episode ≥14 consecutive days was associated with increased odds of death (OR 1.26, 95% CI 1.06-1.48; P = 0.006). CONCLUSION: Remote monitoring data from CIEDs can be used to identify patients at higher risk of all-cause mortality as well as HF events. Distinct from other prognostic scores, this approach is automated and continuously updated.